An exploratory study on applicability of cross project defect prediction approaches to cross-company effort estimation
Author:
Affiliation:
1. Okayama Prefectural University, Japan
2. Ehime University, Japan
Funder
Japan Society for the Promotion of Science
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3416508.3417118
Reference59 articles.
1. Improving Cross-Project Defect Prediction Methods with Data Simplification
2. Applying Cross Project Defect Prediction Approaches to Cross-Company Effort Estimation
3. A replicated assessment and comparison of common software cost modeling techniques
4. Multi-objective Cross-Project Defect Prediction
5. Janez Demšar. 2006. Statistical comparisons of classifiers over multiple data sets. The Journal of Machine Learning Research 7 ( 2006 ) 1-30. Janez Demšar. 2006. Statistical comparisons of classifiers over multiple data sets. The Journal of Machine Learning Research 7 ( 2006 ) 1-30.
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1. An extended study on applicability and performance of homogeneous cross-project defect prediction approaches under homogeneous cross-company effort estimation situation;Empirical Software Engineering;2022-01-27
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